Predicting incursion of plant invaders into Kruger National Park, South Africa : the interplay of general drivers and species-specific factors

Abstract:

BACKGROUND: Overcoming boundaries is crucial for incursion of alien plant species and their successful naturalization and
invasion within protected areas. Previous work showed that in Kruger National Park, South Africa, this process can be
quantified and that factors determining the incursion of invasive species can be identified and predicted confidently. Here
we explore the similarity between determinants of incursions identified by the general model based on a multispecies
assemblage, and those identified by species-specific models. We analyzed the presence and absence of six invasive plant
species in 1.061.5 km segments along the border of the park as a function of environmental characteristics from outside
and inside the KNP boundary, using two data-mining techniques: classification trees and random forests.
PRINCIPAL FINDINGS: The occurrence of Ageratum houstonianum, Chromolaena odorata, Xanthium strumarium, Argemone
ochroleuca, Opuntia stricta and Lantana camara can be reliably predicted based on landscape characteristics identified by
the general multispecies model, namely water runoff from surrounding watersheds and road density in a 10 km radius. The
presence of main rivers and species-specific combinations of vegetation types are reliable predictors from inside the park.
CONCLUSIONS: The predictors from the outside and inside of the park are complementary, and are approximately equally
reliable for explaining the presence/absence of current invaders; those from the inside are, however, more reliable for
predicting future invasions. Landscape characteristics determined as crucial predictors from outside the KNP serve as
guidelines for management to enact proactive interventions to manipulate landscape features near the KNP to prevent
further incursions. Predictors from the inside the KNP can be used reliably to identify high-risk areas to improve the costeffectiveness
of management, to locate invasive plants and target them for eradication.